Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2010
Authors
Tuula Kantola Mikko Vastaranta Xiaowei Yu Paivi Lyytikainen-Saarenmaa Markus Holopainen Mervi Talvitie Sanna Kaasalainen Svein Solberg Juha HyyppäAbstract
Climate change has been observed to be related to the increase of forest insect damages in the boreal zone. The prediction of the changes in the distribution of insect-caused forest damages has become a topical issue in the field of forest research. The common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini caused severe growth losses and tree mortality of Scots pine (Pinus sylvestris L.) (Pinaceae). Logistic regression is commonly used in modelling the probability of occurrence of an event. In this study the logistic regression was investigated for predicting the needle loss of individual Scots pines (pine) using the features derived from airborne laser scanning (ALS) data. The defoliation level of 164 trees was determined subjectively in the field. Statistical ALS features were extracted for single trees and used as independent variables in logistic regression models. Classification accuracy of defoliation was 87.8% as respective kappa-value was 0.82. For comparison, only penetration features were selected and classification accuracy of 78.0% was achieved (kappa=0.56). Based on the results, it is concluded that ALS based prediction of needle losses is capable to provide accurate estimates for individual trees.
Abstract
While forest inventories based on airborne laser scanning data (ALS) using the area based approach (ABA) have reached operational status, methods using the individual tree crown approach (ITC) have basically remained a research issue. One of the main obstacles for operational applications of ITC is biased results often experienced due to segmentation errors. In this article, we propose a new method, called "semi-ITC" that overcomes the main problems related to ITC by imputing ground truth data within crown segments from the nearest neighboring segment. This may be none, one, or several trees. The distances between segments were derived based on a set of explanatory variables using two nonparametric methods, i.e., most similar neighbor inference (MSN) and random forest (RF). RF favored the imputation of common observations in the data set which resulted in significant biases. Main conclusions are therefore based on MSN. The explanatory variables were calculated by means of small footprint ALS and multispectral data. When testing with empirical data the new method compared favorably to the well-known ABA. Another advantage of the new method over the ABA is that it allowed for the modeling of rare tree species. The results of predicting timber volume with the semi-ITC method were unbiased and the root mean squared error (RMSE) on plot level was smaller than the standard deviation of the observed response variables. The relative RMSEs after cross validation using semi-ITC for total volume and volume of the individual species pine, spruce, birch, and aspen on plot level were 17, 38, 40, 101, and 222%, respectively. Due to the unbiasedness of the estimation, this study is a showcase for how to use crown segments resulting from ITC algorithms in a forest inventory context. (C) 2009 Elsevier Inc. All rights reserved.
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J. Brian Hardaker Gudbrand LienAbstract
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Jihong Liu Clarke Carl Jonas Jorge Spetz Sissel Haugslien Merete Dees Roar Moe Dag-Ragnar BlystadAbstract
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Abstract
Coated wooden claddings in building facades are widely used in the Scandinavian countries, and are often preferred to other materials. Wood experience an increasing competition from other materials that are less labor intensive at the construction site and materials with less demand for maintenance thru service life, and makes further development of wooden claddings essential. Growth of discoloring moulds on exposed coated wooden claddings is mainly of aesthetic concern, and is especially disfiguring for light-colored surfaces. Growth of surface fungi often initiates repeated cleaning and shorter maintenance intervals, which in turn increase the total cost of ownership for wooden claddings. Cost and effort of ownership is often an important factor considered when choosing a product, and the traditionally good market situation for wooden claddings is therefore threatened. The development of real-time PCR (polymerase chain reaction) and taxon-specific primers has provided new possibilities for specific detection and quantification of fungi in their natural substrates. In qPCR (quantitative real-time PCR), the accumulation of the PCR product is detected for each amplification cycle. An efficient and reproducible sampling and extraction of DNA is required for a high-throughput qPCR based quantification of discoloring fungi. The authors have now adjusted DNA isolation protocols and optimized real-time PCR assays for species specific detection of fungi frequently found on painted surfaces (Aureobasidium pullulans, Alternaria alternata, Cladosporium cladosporides, Ulocladium atrum).
Abstract
Traditional wood preservatives based on biocides are effective against wood-deteriorating organisms because of their toxicity. By contrast, modified woods are non-toxic by definition. To investigate the efficiency of various wood modifications, quantitative real-time polymerase chain reaction (qPCR) was used to profile the DNA amounts of the white-rot fungus Trametes versicolor (L.) [Lloyd strain CTB 863 A] during an 8-week-long growth period in treated Pinus sylvestris (L.) sapwood. The studied wood was modified by acetylation, furfurylation, and thermal treatment. The traditional wood preservatives bis-(N-cyclohexyldiazeniumdioxy)-copper (Cu-HDO) and chromated copper arsenate (CCA) were used as references, whereas untreated P. sylvestris (L.) sapwood served as a control. The maximum levels of fungal DNA in native wood occurred at the end of the experiment. For all wood treatments, the maximum fungal DNA level was recorded after an incubation period of 2 weeks, followed by a decline until the end of the trial. For the preservative-treated woods, Cu-HDO showed the lowest level of fungal DNA throughout the experiment, indicating that exploratory hyphal growth is limited owing to the phytotoxicity of the treatment. The other treatments did not inhibit the exploratory hyphal growth phase. We conclude that qPCR studies of hyphal growth patterns within wood should provide a powerful tool for evaluating and further optimizing new wood protection systems.